code: def __new__(cls, row_offsets, column_indices, values, shape):
      kwargs = {}
      kwargs["device"] = values.device
      kwargs["dtype"] = values.dtype
      kwargs["layout"] = values.layout
      kwargs["requires_grad"] = values.requires_grad
      assert len(shape) == 3
      assert torch.__version__ > (
          1,
          10,
      ), "SparseCSRTensor requires PyTorch 1.11+"
      return torch.Tensor._make_wrapper_subclass(cls, shape, **kwargs)
  
imports: import torch
  from xformers.ops import masked_matmul
  from xformers.sparse import _csr_ops
  from xformers.sparse.utils import _csr_to_coo, _dense3d_to_sparse, _diffsort, _get_transpose_info, _transpose_with_info
label_desc: Use image node_id 1 for calling the SparseCSRTensor obj's underlying member method code with example usage: obj.__new__(cls, row_offsets, column_indices, values, shape) and returns: torch